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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_hypothesismean4.wasp
Title produced by softwareTesting Mean with known Variance - Sample Size
Date of computationTue, 11 Nov 2008 12:10:58 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/11/t1226430682yo9oj6q7i74cxxk.htm/, Retrieved Mon, 20 May 2024 10:34:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23848, Retrieved Mon, 20 May 2024 10:34:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Testing Mean with known Variance - Critical Value] [Q1 - Critical Value] [2008-11-11 16:59:25] [7dd69dd5bf324136de15cb4f11455bad]
F RMP     [Testing Mean with known Variance - Sample Size] [Q4 - Sample size] [2008-11-11 19:10:58] [e0f4dc76ea1a8276fe566258b977cec4] [Current]
Feedback Forum
2008-11-20 10:38:19 [Tamara Witters] [reply] 
Je berekening met de R-code is helemaal fout, terwijl ook hier de juiste oplossing in je document staat.

oplos:
We zetten de type 2 error op 5% want we willen de pakkans verhogen naar 95%. Maar hiervoor de steekproefgrootte verhogen naar 32466.5. Dit is onhaalbaar en de kostprijs is te hoog.
2008-11-23 10:49:17 [Liese Tormans] [reply] 
Q4: Ook hier is de berekening (link) helemaal verkeerd, terwijl in je document de juiste oplossing staat.

Hier vind je een link met de juiste oplossing
http://www.freestatistics.org/blog/date/2008/Nov/11/t1226411427giut0riueid1vo0.htm

Daarnaast is er ook geen conclusie gevormd.
Om de pakkans te vergroten moeten we de steekproef verhogen tot 95%. We wijzigen dus de Type II error in 0,05. We zien dan dat we een sample size van 32.466 moeten nemen om de pakkans te verhogen naar 95%. Dit is praktisch niet haalbaar omdat het enorm veel tijd en geld zou kosten.

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Dataset

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23848&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23848&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23848&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Testing Mean with known Variance
population variance0.36
null hypothesis about mean5.2
alternative hypothesis about mean5.4
type I error0.05
type II error0.05
sample size97.3995643474338

\begin{tabular}{lllllllll}
\hline
Testing Mean with known Variance \tabularnewline
population variance & 0.36 \tabularnewline
null hypothesis about mean & 5.2 \tabularnewline
alternative hypothesis about mean & 5.4 \tabularnewline
type I error & 0.05 \tabularnewline
type II error & 0.05 \tabularnewline
sample size & 97.3995643474338 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23848&T=1

[TABLE]
[ROW][C]Testing Mean with known Variance[/C][/ROW]
[ROW][C]population variance[/C][C]0.36[/C][/ROW]
[ROW][C]null hypothesis about mean[/C][C]5.2[/C][/ROW]
[ROW][C]alternative hypothesis about mean[/C][C]5.4[/C][/ROW]
[ROW][C]type I error[/C][C]0.05[/C][/ROW]
[ROW][C]type II error[/C][C]0.05[/C][/ROW]
[ROW][C]sample size[/C][C]97.3995643474338[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23848&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23848&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Testing Mean with known Variance
population variance0.36
null hypothesis about mean5.2
alternative hypothesis about mean5.4
type I error0.05
type II error0.05
sample size97.3995643474338


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.36 ; par2 = 5.2 ; par3 = 5.4 ; par4 = 0.05 ; par5 = 0.05 ;
Parameters (R input):
par1 = 0.36 ; par2 = 5.2 ; par3 = 5.4 ; par4 = 0.05 ; par5 = 0.05 ;
R code (references can be found in the software module):
par1<-as.numeric(par1)
par2<-as.numeric(par2)
par3<-as.numeric(par3)
par4<-as.numeric(par4)
par5<-as.numeric(par5)
c <- 'NA'
csn <- abs(qnorm(par5))
if (par2 == par3)
{
conclusion <- 'Error: the null hypothesis and alternative hypothesis must not be equal.'
}
ua <- abs(qnorm(par4))
ub <- qnorm(par5)
c <- (par2+ua/ub*(-par3))/(1-(ua/ub))
sqrtn <- ua*sqrt(par1)/(c - par2)
samplesize <- sqrtn * sqrtn
ua
ub
c
sqrtn
samplesize
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ht_mean_knownvar.htm','Testing Mean with known Variance','learn more about Statistical Hypothesis Testing about the Mean when the Variance is known'),2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'population variance',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'null hypothesis about mean',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alternative hypothesis about mean',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'type I error',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'type II error',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('ht_mean_knownvar.htm#ex4','sample size','example'),header=TRUE)
a<-table.element(a,samplesize)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')